乐胖代购免代理版

{"id":"https://openalex.org/W4220665615","doi":"https://doi.org/10.3390/s22062224","title":"An Ensemble Learning Model for COVID-19 Detection from Blood Test Samples","display_name":"An Ensemble Learning Model for COVID-19 Detection from Blood Test Samples","publication_year":2022,"publication_date":"2022-03-13","ids":{"openalex":"https://openalex.org/W4220665615","doi":"https://doi.org/10.3390/s22062224","pmid":"https://pubmed.ncbi.nlm.nih.gov/35336395"},"language":"en","primary_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22062224","pdf_url":"https://www.mdpi.com/1424-8220/22/6/2224/pdf?version=1647177155","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true},"type":"article","type_crossref":"journal-article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/22/6/2224/pdf?version=1647177155","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5032655161","display_name":"Olusola Abayomi\u2010Alli","orcid":"https://orcid.org/0000-0003-2513-5318"},"institutions":[{"id":"https://openalex.org/I172574986","display_name":"Kaunas University of Technology","ror":"https://ror.org/01me6gb93","country_code":"LT","type":"education","lineage":["https://openalex.org/I172574986"]}],"countries":["LT"],"is_corresponding":false,"raw_author_name":"Olusola O. Abayomi-Alli","raw_affiliation_strings":["Department of Software Engineering, Kaunas University of Technology, 51368 Kaunas, Lithuania"],"affiliations":[{"raw_affiliation_string":"Department of Software Engineering, Kaunas University of Technology, 51368 Kaunas, Lithuania","institution_ids":["https://openalex.org/I172574986"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042653526","display_name":"Robertas Dama\u0161evi\u010dius","orcid":"https://orcid.org/0000-0001-9990-1084"},"institutions":[{"id":"https://openalex.org/I172574986","display_name":"Kaunas University of Technology","ror":"https://ror.org/01me6gb93","country_code":"LT","type":"education","lineage":["https://openalex.org/I172574986"]}],"countries":["LT"],"is_corresponding":true,"raw_author_name":"Robertas Dama\u0161evi\u010dius","raw_affiliation_strings":["Department of Software Engineering, Kaunas University of Technology, 51368 Kaunas, Lithuania"],"affiliations":[{"raw_affiliation_string":"Department of Software Engineering, Kaunas University of Technology, 51368 Kaunas, Lithuania","institution_ids":["https://openalex.org/I172574986"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039508726","display_name":"Rytis Maskeli\u016bnas","orcid":"https://orcid.org/0000-0002-2809-2213"},"institutions":[{"id":"https://openalex.org/I172574986","display_name":"Kaunas University of Technology","ror":"https://ror.org/01me6gb93","country_code":"LT","type":"education","lineage":["https://openalex.org/I172574986"]}],"countries":["LT"],"is_corresponding":false,"raw_author_name":"Rytis Maskeli\u016bnas","raw_affiliation_strings":["Department of Multimedia Engineering, Kaunas University of Technology, 51368 Kaunas, Lithuania"],"affiliations":[{"raw_affiliation_string":"Department of Multimedia Engineering, Kaunas University of Technology, 51368 Kaunas, Lithuania","institution_ids":["https://openalex.org/I172574986"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064136287","display_name":"Sanjay Misra","orcid":"https://orcid.org/0000-0002-3556-9331"},"institutions":[{"id":"https://openalex.org/I19923696","display_name":"\u00d8stfold University College","ror":"https://ror.org/04gf7fp41","country_code":"NO","type":"education","lineage":["https://openalex.org/I19923696"]}],"countries":["NO"],"is_corresponding":false,"raw_author_name":"Sanjay Misra","raw_affiliation_strings":["Department of Computer Science and Communication, Ostfold University College, 3001 Halden, Norway"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Communication, Ostfold University College, 3001 Halden, Norway","institution_ids":["https://openalex.org/I19923696"]}]}],"institution_assertions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5042653526"],"corresponding_institution_ids":["https://openalex.org/I172574986"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2598,"provenance":"doaj"},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2598,"provenance":"doaj"},"fwci":7.186,"has_fulltext":true,"fulltext_origin":"pdf","cited_by_count":32,"citation_normalized_percentile":{"value":0.999944,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":"22","issue":"6","first_page":"2224","last_page":"2224"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11754","display_name":"SARS-CoV-2 detection and testing","score":0.9922,"subfield":{"id":"https://openalex.org/subfields/2725","display_name":"Infectious Diseases"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9852,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/adaboost","display_name":"AdaBoost","score":0.6963156},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble Learning","score":0.6666943},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.46543303},{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.43453676},{"id":"https://openalex.org/keywords/quadratic-classifier","display_name":"Quadratic classifier","score":0.43392992},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.42043576}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8000629},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.705343},{"id":"https://openalex.org/C141404830","wikidata":"https://www.wikidata.org/wiki/Q2823869","display_name":"AdaBoost","level":3,"score":0.6963156},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.6961143},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6842867},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.6666943},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.5825704},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.5759302},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.52314246},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.4820455},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.46972337},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.46543303},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.43453676},{"id":"https://openalex.org/C52620605","wikidata":"https://www.wikidata.org/wiki/Q7268357","display_name":"Quadratic classifier","level":3,"score":0.43392992},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.42043576},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40384465},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.38776642}],"mesh":[{"descriptor_ui":"D001185","descriptor_name":"Artificial Intelligence","qualifier_ui":"","qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000086382","descriptor_name":"COVID-19","qualifier_ui":"","qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D001499","descriptor_name":"Bayes Theorem","qualifier_ui":"","qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000086382","descriptor_name":"COVID-19","qualifier_ui":"Q000175","qualifier_name":"diagnosis","is_major_topic":false},{"descriptor_ui":"D006403","descriptor_name":"Hematologic Tests","qualifier_ui":"","qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":"","qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":"","qualifier_name":null,"is_major_topic":false}],"locations_count":5,"locations":[{"is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22062224","pdf_url":"https://www.mdpi.com/1424-8220/22/6/2224/pdf?version=1647177155","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true},{"is_oa":false,"landing_page_url":"https://doaj.org/article/189f5192eb934c81946b60e6561cd2c0","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},{"is_oa":true,"landing_page_url":"https://hdl.handle.net/11250/3036867","pdf_url":"https://hiof.brage.unit.no/hiof-xmlui/bitstream/11250/3036867/1/MisraAnEnsemble2022.pdf","source":{"id":"https://openalex.org/S4306401716","display_name":"Duo Research Archive (University of Oslo)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I184942183","host_organization_name":"University of Oslo","host_organization_lineage":["https://openalex.org/I184942183"],"host_organization_lineage_names":["University of Oslo"],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true},{"is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8955536","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":["National Institutes of Health"],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true},{"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35336395","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":["National Institutes of Health"],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22062224","pdf_url":"https://www.mdpi.com/1424-8220/22/6/2224/pdf?version=1647177155","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true},"sustainable_development_goals":[{"score":0.58,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":66,"referenced_works":["https://openalex.org/W1961147827","https://openalex.org/W2148143831","https://openalex.org/W2496114304","https://openalex.org/W2560528144","https://openalex.org/W2615421112","https://openalex.org/W2741016737","https://openalex.org/W2799985340","https://openalex.org/W2970602317","https://openalex.org/W3001195213","https://openalex.org/W3009333463","https://openalex.org/W3010522809","https://openalex.org/W3013758358","https://openalex.org/W3014846667","https://openalex.org/W3014903039","https://openalex.org/W3015381159","https://openalex.org/W3015433395","https://openalex.org/W3025069580","https://openalex.org/W3025576489","https://openalex.org/W3025646590","https://openalex.org/W3027575153","https://openalex.org/W3028067578","https://openalex.org/W3032138494","https://openalex.org/W3033756580","https://openalex.org/W3034711653","https://openalex.org/W3038925693","https://openalex.org/W3041463877","https://openalex.org/W3046858365","https://openalex.org/W3048479592","https://openalex.org/W3062600242","https://openalex.org/W3080441768","https://openalex.org/W3092172475","https://openalex.org/W3093955131","https://openalex.org/W3094265554","https://openalex.org/W3095676075","https://openalex.org/W3096451520","https://openalex.org/W3101978680","https://openalex.org/W3104810384","https://openalex.org/W3105837102","https://openalex.org/W3107806617","https://openalex.org/W3110677219","https://openalex.org/W3110804228","https://openalex.org/W3120192536","https://openalex.org/W3122601055","https://openalex.org/W3123695557","https://openalex.org/W3125645332","https://openalex.org/W3125771089","https://openalex.org/W3132163368","https://openalex.org/W3135919189","https://openalex.org/W3137637229","https://openalex.org/W3146264788","https://openalex.org/W3165312480","https://openalex.org/W3165608771","https://openalex.org/W3168811973","https://openalex.org/W3174895568","https://openalex.org/W3182067642","https://openalex.org/W3184886727","https://openalex.org/W3202232851","https://openalex.org/W3204116175","https://openalex.org/W3208239477","https://openalex.org/W3209832830","https://openalex.org/W4200117063","https://openalex.org/W4200121693","https://openalex.org/W4205179063","https://openalex.org/W4205619076","https://openalex.org/W4211056171","https://openalex.org/W4231883360"],"related_works":["https://openalex.org/W4390916549","https://openalex.org/W4382315444","https://openalex.org/W4381298925","https://openalex.org/W4298012357","https://openalex.org/W4285213578","https://openalex.org/W4233259193","https://openalex.org/W2915435096","https://openalex.org/W2600353413","https://openalex.org/W2097856925","https://openalex.org/W1997565450"],"abstract_inverted_index":{"Current":[0],"research":[1,64],"endeavors":[2],"in":[3,11,33,65],"the":[4,12,15,60,67,82,217,226,236,241],"application":[5],"of":[6,14,36,57,93,195,202,210,214,225],"artificial":[7],"intelligence":[8],"(AI)":[9],"methods":[10],"diagnosis":[13],"COVID-19":[16,37,94,106,228,247],"disease":[17],"has":[18],"proven":[19],"indispensable":[20],"with":[21,231],"very":[22],"promising":[23,27],"results.":[24,100],"Despite":[25],"these":[26],"results,":[28],"there":[29],"are":[30],"still":[31],"limitations":[32],"real-time":[34],"detection":[35,92,107,229],"using":[38,95,124,235],"reverse":[39],"transcription":[40],"polymerase":[41],"chain":[42],"reaction":[43],"(RT-PCR)":[44],"test":[45,99],"data,":[46],"such":[47],"as":[48,131,141],"limited":[49],"datasets,":[50],"imbalance":[51],"classes,":[52],"a":[53,132,142,192,207],"high":[54],"misclassification":[55],"rate":[56],"models,":[58],"and":[59,70,80,135,151,166,173,189,197,212],"need":[61],"for":[62,90],"specialized":[63],"identifying":[66],"best":[68],"features":[69],"thus":[71],"improving":[72],"prediction":[73,88],"rates.":[74],"This":[75],"study":[76],"aims":[77],"to":[78,86,112,115],"investigate":[79],"apply":[81],"ensemble":[83,103,183],"learning":[84,139,184],"approach":[85,230],"develop":[87],"models":[89,130],"effective":[91],"routine":[96],"laboratory":[97],"blood":[98],"Hence,":[101],"an":[102,182],"machine":[104,138],"learning-based":[105],"system":[108],"is":[109],"presented,":[110],"aiming":[111],"aid":[113],"clinicians":[114],"diagnose":[116],"this":[117],"virus":[118],"effectively.":[119],"The":[120,223],"experiment":[121],"was":[122],"conducted":[123],"custom":[125],"convolutional":[126],"neural":[127],"network":[128],"(CNN)":[129],"first-stage":[133],"classifier":[134],"15":[136],"supervised":[137],"algorithms":[140],"second-stage":[143],"classifier:":[144],"K-Nearest":[145],"Neighbors,":[146],"Support":[147],"Vector":[148],"Machine":[149],"(Linear":[150],"RBF),":[152],"Naive":[153],"Bayes,":[154],"Decision":[155],"Tree,":[156],"Random":[157],"Forest,":[158],"MultiLayer":[159],"Perceptron,":[160],"AdaBoost,":[161],"ExtraTrees,":[162],"Logistic":[163],"Regression,":[164],"Linear":[165],"Quadratic":[167],"Discriminant":[168],"Analysis":[169],"(LDA/QDA),":[170],"Passive,":[171],"Ridge,":[172],"Stochastic":[174],"Gradient":[175],"Descent":[176],"Classifier.":[177],"Our":[178],"findings":[179],"show":[180],"that":[181,240],"model":[185],"based":[186],"on":[187,216],"DNN":[188],"ExtraTrees":[190],"achieved":[191],"mean":[193,208],"accuracy":[194,209],"99.28%":[196,211],"area":[198],"under":[199],"curve":[200],"(AUC)":[201],"99.4%,":[203],"while":[204],"AdaBoost":[205],"gave":[206],"AUC":[213],"98.8%":[215],"San":[218],"Raffaele":[219],"Hospital":[220],"dataset,":[221],"respectively.":[222],"comparison":[224],"proposed":[227,242],"other":[232,246],"state-of-the-art":[233],"approaches":[234],"same":[237],"dataset":[238],"shows":[239],"method":[243],"outperforms":[244],"several":[245],"diagnostics":[248],"methods.":[249]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4220665615","counts_by_year":[{"year":2024,"cited_by_count":16},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":6}],"updated_date":"2025-01-07T22:13:52.064947","created_date":"2022-04-03"}